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Role of AI techniques and deep learning in analyzing the critical health conditions

机译:AI技术与深入学习在分析关键健康状况时的作用

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The role of a healthcare practitioner is to diagnose a disease and find an optimum means for suitable treatment. This has been the most challenging task over the years. The researchers have been developing intelligent tools for providing support in taking medical decision. The application of AI in different health scenario strengthen the mechanism for finding a better treatment plan. The authors share some recent advancements in this domain. The role of artificial intelligence in Indian healthcare system has also been discussed. The paper analyzes the use of different AI techniques like fuzzy logic, Artificial Neural Networks, Particle Swarm Optimization and Fuzzy Neural in critical health scenario. A detail literature review has been provided in this context. The disease taken into consideration are cancer, TB, diabetes, malaria, orthopedics, obesity and disease specific to elderly people. The purpose of this article is to find the relevance of various techniques of AI in different critical health scenarios. A comparative analysis is done based on the publications since 1995. The challenges and risks associated with the usage of AI in healthcare has been analysed and suggestions made for making the analysis in the health domain more accurate and effective. Further the concept of deep learning has also been explained and its inculcation with the medical domain is discussed.
机译:医疗保健医生的作用是诊断疾病并找到适合治疗的最佳手段。这是多年来最具挑战性的任务。研究人员一直在开发智能工具,以提供医疗决定的支持。 AI在不同的健康情景中的应用加强了寻找更好待遇计划的机制。作者分享了该领域的一些最新进步。人工智能在印度医疗系统中的作用也已经讨论过。本文分析了不同AI技术,如模糊逻辑,人工神经网络,粒子群优化和模糊神经中的临界健康情景。在此背景下提供了详细文献综述。考虑的疾病是癌症,结核病,糖尿病,疟疾,骨科,肥胖症和老年人特异的疾病。本文的目的是在不同危重健康情景中找到AI各种技术的相关性。自1995年以来,基于出版物进行了比较分析。分析了与医疗保健中AI的使用相关的挑战和风险,并提出了对卫生领域的分析更准确和有效的建议。此外,还讨论了深度学习的概念,并讨论了与医疗领域的灌生。

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